Robots On 'Jeopardy'

Earlier this year, IBM announced that its research labs were designing a computer system that is scheduled to compete against human opponents in the well-known TV quiz show Jeopardy. The great fanfare (among technology fans, in any event) accompanying IBM's announcement cannot but strike many of us who were there at the dawn of the commercial digital explosion as a small irony.

Fifty years ago,
IBM
was already a major player in the then minor arena of artificial intelligence. The first modestly skillful full-board chess program; the first checkers program, which defeated a regional champion; a program able to prove theorems in Euclidean plane geometry, which could pass the problem-solving section of a New York State high school regents examination; and serious research in both speech and character recognition were all part of the IBM Research playbook.

Many among IBM management, however, felt that the climate of mid-20th century America following the Great Depression would not support the threat of an entirely new class of machines that might challenge and possibly replace humans at some tasks. Business machine companies were fearful of arousing a neo-Luddite rebellion. After all, even the antediluvian computers then available had brought on a great deal of abuse from some who saw their jobs (and their dignity) in jeopardy.

Despite its many early contributions to the nascent discipline, IBM adopted a public posture of skepticism towards the prospects of realizing truly intelligent behavior in machines, electing instead to hide behind the self-evident claim that "machines can only do what we tell them to do." Meanwhile, sotto voce, the message emerging from IBM's research labs was that "we can tell machines to be smart!"

IBM chose to mute those achievements, continuing to maintain a relatively low AI profile until the last decade, when it burst into public awareness with the unveiling of its chess-playing supercomputer Deep Blue to challenge chess grandmaster, and then world champion, Garry Kasparov. Deep Blue emerged as the victor in a pair of disputed matches.

And now, IBM once again captures the limelight with an announcement that a much advanced successor to Deep Blue, will come closer than ever before to offering an answer in the affirmative to what has become the classical (if not universally accepted) formulation of the philosophical question "Can machines think?" the Turing Imitation Game.

In 1950, the brilliant British mathematician Alan M. Turing--celebrated for, among other major achievements, his contributions to mathematics and the theory of computation, and a crucial role he played during World War II in breaking the code of the German Enigma cipher--published a paper in the journal Mind with the title "Computing Machinery and Intelligence." In the article, Turing argues that any meaningful discussion of machine intelligence demands an operational definition of the concept of thinking, in humans as well as in machines. The Imitation Game, first proposed in 1950, has since undergone serial modification, but in substance, it was and remains a test whereby a hidden machine attempts to convince a (human) interrogator that it, rather that the hidden human challenger in the next room, is indeed the human.

It seems clear that the skills to be imparted to Deep Blue's successor (appropriately christened Blue Gene, part of an ongoing project called DeepQA) must go well beyond the realm of natural language parsing and database search if the computer is to succeed in assuming a convincing human appearance in competition with a real live contestant in a game with the format and broad literary horizons of Jeopardy. Foremost among these skills is the ability to understand the questions that will be posed in the context of the game, here a TV entertainment, but construed in a broader sense, the complex and always challenging game of human interaction. If the members of IBM's DeepQA project are able to realize that objective, then I would accept a creditable performance by Blue Gene as a contestant on Jeopardy as an affirmative answer to the question "can machines think?" Were Turing alive, I'm willing to bet that he would too.

Herbert Gelernter is professor emeritus of computer science at SUNY Stony Brook. Over the years, his research has encompassed the areas of theoretical physics, artificial intelligence, expert systems and machine learning. His most recent work has been in the design of an intelligent computer system for the discovery of synthesis pathways for complex organic compounds starting from readily available materials.